arXiv subjects

Luciano Stucchi

Publications and source records attributed to Luciano Stucchi.

6 recordsLinked to original sources

arXiv2026

Structural Analysis of Journal Columns Using Ordinal Patterns and Information-Theoretic Measures

Source attribution in journalistic text is typically approached through semantic representations, such as term weighting or neural embeddings. These approaches capture topical content, but usually overlook how a text is organized as a sequence. Here, we show that purely structural, content-independent features can discriminate between news sources on their own. We converted articles from fourteen Peruvian online newspapers into numerical sequences using two independent encodings, word length and lexical frequency. Then, we analyzed each of them through ordinal pattern analysis, computing pattern and transition probabilities, permutation entropy, disequilibrium, and statistical complexity. Both encodings yield non-uniform ordinal pattern distributions, well-defined preferential transitions, and coherent entropy complexity signatures across sources. Unsupervised clustering recovers three coherent groups in the feature space, and supervised classifiers trained on these features achieve accuracy up to 0.99, which remains stable even under substantial feature reduction. The consistency of these results across two structurally unrelated encodings strongly indicates that ordinal features capture a genuine dynamical fingerprint of each source's writing style rather than an artifact of either representation, which extends this framework to Spanish-language journalism, a setting that remains comparatively underexplored in complexity-based text analysis.

physics.soc-ph↗

arXiv2026

When one protocol fits none: Self-organized network routing through evolutionary game dynamics

Packet routing on scale-free networks faces a fundamental trade-off: shortest-path routing is efficient at low demand but funnels traffic through hubs and jams early, whereas congestion-aware routing postpones jamming at the price of a sharper collapse. Since neither paradigm dominates across the full range of traffic load, here we ask whether the appropriate balance can emerge endogenously rather than being imposed by design. To answer this, we recast adaptive packet routing on networks as an evolutionary game letting a heterogeneous population of strategies compete for prevalence under selection pressure generated by their own performance. We study this competition under two formalisms (strategy anchored to the packet or to the generating node), global and local update rules, and two payoff metrics. Across every implementation the evolutionary dynamics yield the same outcome: the jamming transition is delayed relative to shortest-path routing while the violent collapse of fixed congestion-aware routing is avoided. This improvement emerges spontaneously, without centralized coordination or global information. Crucially, under local update rules, the node-level volatility of strategy choices peaks sharply at the transition, furnishing a purely local early-warning signal of imminent jamming that requires no global monitoring.

physics.soc-ph↗

arXiv2025

Quantifying Emergent Behaviors in Agent-Based Models using Mean Information Gain

Emergent behaviors are a defining feature of complex systems, yet their quantitative characterization remains an open challenge, as traditional classifications rely mainly on visual inspection of spatio-temporal patterns. In this Letter, we propose using the Mean Information Gain (MIG) as a metric to quantify emergence in Agent-Based Models. The MIG is a conditional entropy-based metric that quantifies the lack of information about other elements in a structure given certain known properties. We apply it to a multi-agent biased random walk that reproduces Wolfram's four behavioral classes and show that MIG differentiates these behaviors. This metric reconnects the analysis of emergent behaviors with the classical notions of order, disorder, and entropy, thereby enabling the quantitative classification of regimes as convergent, periodic, complex, and chaotic. This approach overcomes the ambiguity of qualitative inspection near regime boundaries, particularly in large systems, and provides a compact, extensible framework for identifying and comparing emergent behaviors in complex systems.

physics.soc-ph↗

arXiv2025

TAMBO: A Deep-Valley Neutrino Observatory

Although the field of neutrino astronomy has blossomed in the last decade, physicists have struggled to fully map the high-energy neutrino sky. TAMBO, a mountain-based neutrino observatory, aims to solve that issue -- and find clues of new physics along the way.

astro-ph.HE↗

arXiv2022

Prevalence of mutualism in a simple model of microbial co-evolution

Evolutionary transitions among ecological interactions are widely known, although their detailed dynamics remain absent for most population models. Adaptive dynamics has been used to illustrate how the parameters of population models might shift through evolution, but within an ecological regime. Here we use adaptive dynamics combined with a generalised logistic model of population dynamics to show that transitions of ecological interactions might appear as a consequence of evolution. To this purpose we introduce a two-microbial toy model in which population parameters are determined by a bookkeeping of resources taken from (and excreted to) the environment, as well as from the byproducts of the other species. Despite its simplicity, this model exhibits all kinds of potential ecological transitions, some of which resemble those found in nature. Overall, the model shows a clear trend toward the emergence of mutualism.

q-bio.PE↗

arXiv2019

Pattern formation induced by intraspecific interactions in a predator-prey system

Differential diffusion is a source of instability in population dynamics systems when species diffuse with different rates. Predator-prey systems show this instability only under certain specific conditions, usually requiring Holling-type functionals involved. Here we study the effects of intraspecific cooperation and competition on diffusion-driven instability in a predator-prey system with a different structure. We conduct the analysis on a generalized population dynamics that bounds intraspecific and interspecific interactions with Verhulst-type saturation terms instead of Holling-type functionals. We find that instability occurs due to the intraspecific saturation or intraspecific interactions, both cooperative and competitive. We present numerical simulations and show spatial patterns due to diffusion.

q-bio.PE↗